Panel interview with senior members of some prominent healthcare AI startups #GiantHealthEvent

All these companies use machine learning in different ways either to analyse the genome, diagnostic/surgical implications or helping patients directly.

All of the panel agree that AI is coming back after going through a ‘nuclear’ winter.

Eagle Genomics feel that by 2025 there will be over 250 million patients with their genomes sequenced. This constitutes several zetabytes of data. This cannot be analysed by humans but only machines. We have a burgeoning data management crisis that can be solved in no other way. We need to turn big data into actionable insights.

Babylon health say they want to make healthcare affordable to all – that is their vision. They believe in augmenting doctors and making them safer. Babylon feel the biggest need is in Africa. That is why they are working in Rwanda because the needs are so great.

They think that in the next 5 years there needs to be some sort of regulatory mechanism to govern the use of AI diagnostics. They want to improve the productivity of doctors not replace them.

Touch surgery feel that humans alone cannot deal with all the data alone. They feel that it is essential to use that data in order to learn how to make their product as good as they can. Currently they are trying to use machine learning to improve the user experience and training. They believe that the technology should also help the surgeon in the same way that power-assisted steering and GPS enhance the driving experience.

Myrecovery are analysing how their users are using the apps as well to try and predict their recovery. A lot of people complained about the US election predictions. Garbage in = garbage out. Longer term they see it as a core asset to the business. They feel that the present situation is unsustainable. We can’t compete with robots any more, we need to work with them in order to get the job done.

Creation feel that it will be essential in the future but at the present are focusing on building data sets and getting them verified by medical professionals. They talked about developing a system that could analyse a photo via a network – like instagram for medical diagnosis. They feel that doctors use social media quite a lot. Sometimes they have found doctors answering individual patients on social media. They feel the barriers are breaking down. They also sited the microbiome. He talked about machine sentiment analysis and how it is currently largely useless. Most ‘AI’ is still heavily dependant on human interaction to make it work but in the future this won’t be the case.

Then Charlie asked the panel what advice they would give to tech startups thinking about working in this field. Their advice was:

Get good at selling yourself.

You need to be in it for the long haul. (We are in the middle of a revolution).